Decoding Object Depth from the Macaque IT Cortex: Temporal Dynamics and Insights for ANN Models
Esna Mualla Gunay, Kohitij Kar · COSYNE 2025
Recent studies have demonstrated that the inferior temporal (IT) cortex of macaques encodes various attributes of visual objects, including identity, size, position, and pose (Hong et al., 2016). However, the representation of object depth within IT has remained relatively unexplored. In this study, we investigate whether monocular depth information can be decoded from the distributed population activity across the macaque IT cortex and artificial neural network (ANN) models of the macaque ventral stream. Using 465 single-object images from the Microsoft COCO dataset, annotated with depth inf
ePoster · Neuroscience